Timed and Probabilistic Automata for Automatic Animal Call Recognition

Automatic Call Recognition is vital for environmental monitoring. Patten recognition has been applied in automatic species recognition for years. However, few studies have applied formal syntactic methods to species call structure analysis. This paper introduces a novel method to adopt timed and probabilistic automata in automatic species recognition based upon acoustic components as the primitives. We demonstrate this through one kind of birds in Australia: Eastern Yellow Robin.

Automatic Audio Segmentation Using the Generalized Likelihood Ratio

This paper presents a novel technique for segmenting an audio stream into homogeneous regions according to speaker identities, background noise, music, environmental and channel conditions. Audio segmentation is useful in audio diarization systems, which aim to annotate an input audio stream with information that attributes temporal regions of the audio into their specific sources. The segmentation method introduced in this paper is performed using the Generalized Likelihood Ratio (GLR), computed between two adjacent sliding windows over preprocessed speech. This approach is inspired by the popular segmentation method proposed by the pioneering work of Chen and Gopalakrishnan, using the Bayesian Information Criterion (BIC) with an expanding search window. This paper will aim to identify and address the shortcomings associated with such an approach. The result obtained by the proposed segmentation strategy is evaluated on the 2002 Rich Transcription (RT-02) Evaluation dataset, and a miss rate of 19.47% and a false alarm rate of 16.94% is achieved at the optimal threshold.

Student or scholar? Transforming identities through a research writing group

This article explores the role a writing group played in influencing the scholarly identities of a group of doctoral students by fostering their writing expertise. While the interest in writing groups usually centres on their potential to support doctoral students to publish, few studies have been conducted and written by the students themselves. Using a situated learning perspective on identity, we explore the connection that emerged between our perceptions of ourselves as developing expertise as scholarly writers and the function of the writing group as a dynamic space for transforming our identities. Findings show that our writing group served as a flexible and interactive Community of Practice (CoP) that shaped critical and durable shifts in identity amongst members.

Creative writing in recovery from severe mental illness

There is evidence that creative writing forms an important part of the recovery experience of people affected by severe mental illness. In this paper, we consider theoretical models that explain how creative writing might contribute to recovery, and we discuss the potential for creative writing in psychosocial rehabilitation. We argue that the rehabilitation benefits of creative writing might be optimized through focus on process and technique in writing, rather than content, and that consequently, the involvement of professional writers might be important. We describe a pilot workshop that deployed these principles and was well-received by participants. Finally, we make recommendations regarding the role of creative writing in psychosocial rehabilitation for people recovering from severe mental illness and suggest that the development of an evidence base regarding the effectiveness of creative writing is a priority.

The Cambridge companion to creative writing [Edited book]

Creative writing has become a highly professionalised academic discipline, with popular courses and prestigious degree programmes worldwide. This book is a must for all students and teachers of creative writing, indeed for anyone who aspires to be a published writer. It engages with a complex art in an accessible manner, addressing concepts important to the rapidly growing field of creative writing, while maintaining a strong craft emphasis, analysing exemplary models of writing and providing related writing exercises. Written by professional writers and teachers of writing, the chapters deal with specific genres or forms – ranging from the novel to new media – or with significant topics that explore the cutting edge state of creative writing internationally (including creative writing and science, contemporary publishing and new workshop approaches).

Life writing

Two hundred years ago life writing was already highly popular in the form of autobiography, memoir, biography, journals, essays and diaries. It now commands a huge share of the publishing market, as there is an enormous demand from readers for narratives based directly on 'real lives'. There is a lot of common ground between the two main forms - autobiography/memoir and biography: both require skilled storytelling [rather than listing facts and events], research and imagination. The quality of the writing itself is crucial to the impact on the reader. A person can have an existing, worthy life but unfortunately write about it (or be written about) in a dull way. And how a person is remembered and valued can be a factor of life writing about or by them. This chapter will define and contextualise life writing, look at specific detailed examples, and offer guidance on how to write effectively.

Shut up and write! Some surprising uses of cafes and crowds in doctoral writing

This chapter discusses a ‘writing movement’, which is currently occurring in various parts of Australia through the support of social media. A concept emerging from the café scene in San Francisco, ‘Shut Up and Write!’ is a meetup group that brings writers together at a specific time and place to write side by side, thus making writing practice, social. This concept has been applied to the academic environment and our case-study explores the positive outcomes in two locations: RMIT University and Queensland University of Technology. This informal learning practice can be implemented to assist research students in developing academic skills.

Using static analysis for automatic assessment and mitigation of unwanted and malicious activities within Android applications

In the last decade, smartphones have gained widespread usage. Since the advent of online application stores, hundreds of thousands of applications have become instantly available to millions of smart-phone users. Within the Android ecosystem, application security is governed by digital signatures and a list of coarse-grained permissions. However, this mechanism is not fine-grained enough to provide the user with a sufficient means of control of the applications' activities. Abuse of highly sensible private information such as phone numbers without users' notice is the result. We show that there is a high frequency of privacy leaks even among widely popular applications. Together with the fact that the majority of the users are not proficient in computer security, this presents a challenge to the engineers developing security solutions for the platform. Our contribution is twofold: first, we propose a service which is able to assess Android Market applications via static analysis and provide detailed, but readable reports to the user. Second, we describe a means to mitigate security and privacy threats by automated reverse-engineering and refactoring binary application packages according to the users' security preferences.

Effects of eco-driving instructions using a vehicle with automatic transmission on urban roads

Eco-driving instructions could reduce fuel consumption to up to 20% (EcoMove, 2010). Participants (N=13) drove an instrumented vehicle (i.e. Toyota Camry 2007) with an automatic transmission. Fuel consumption of the participants were compared before and after they received eco-driving instructions. Participants drove the same vehicle on the same urban route under similar traffic conditions. Results show that, on free flow sections of the track, all participants drove slightly faster (on average, 0.7 Km/h faster), during the lap for which they were instructed to drive in an eco-friendly manner as compared to when they were not given the eco-driving instruction. Suprisingly, eco-driving instructions increased the RPM significantly in most cases. Fuel consumption slightly decreased (6%) after the eco-driving instructions. We have found strong evidence showing that the fuel saving observed in our experiment (urban environment, automatic transmission) fall short of the 20% reduction claimed in other international trials.

Dermal fibroblast infiltration of poly(ε-caprolactone) scaffolds fabricated by melt electrospinning in a direct writing mode

Melt electrospinning in a direct writing mode is a recent additive manufacturing approach to fabricate porous scaffolds for tissue engineering applications. In this study, we describe porous and cell-invasive poly (ε-caprolactone) scaffolds fabricated by combining melt electrospinning and a programmable x–y stage. Fibers were 7.5 ± 1.6 µm in diameter and separated by interfiber distances ranging from 8 to 133 µm, with an average of 46 ± 22 µm. Micro-computed tomography revealed that the resulting scaffolds had a highly porous (87%), three-dimensional structure. Due to the high porosity and interconnectivity of the scaffolds, a top-seeding method was adequate to achieve fibroblast penetration, with cells present throughout and underneath the scaffold. This was confirmed histologically, whereby a 3D fibroblast-scaffold construct with full cellular penetration was produced after 14 days in vitro. Immunohistochemistry was used to confirm the presence and even distribution of the key dermal extracellular matrix proteins, collagen type I and fibronectin. These results show that melt electrospinning in a direct writing mode can produce cell invasive scaffolds, using simple top-seeding approaches.

Robust automatic speaker linking and attribution

This research makes a major contribution which enables efficient searching and indexing of large archives of spoken audio based on speaker identity. It introduces a novel technique dubbed as “speaker attribution” which is the task of automatically determining ‘who spoke when?’ in recordings and then automatically linking the unique speaker identities within each recording across multiple recordings. The outcome of the research will also have significant impact in improving the performance of automatic speech recognition systems through the extracted speaker identities.

Automatic query expansion : a structural linguistic perspective

A user’s query is considered to be an imprecise description of their information need. Automatic query expansion is the process of reformulating the original query with the goal of improving retrieval effectiveness. Many successful query expansion techniques ignore information about the dependencies that exist between words in natural language. However, more recent approaches have demonstrated that by explicitly modeling associations between terms significant improvements in retrieval effectiveness can be achieved over those that ignore these dependencies. State-of-the-art dependency-based approaches have been shown to primarily model syntagmatic associations. Syntagmatic associations infer a likelihood that two terms co-occur more often than by chance. However, structural linguistics relies on both syntagmatic and paradigmatic associations to deduce the meaning of a word. Given the success of dependency-based approaches and the reliance on word meanings in the query formulation process, we argue that modeling both syntagmatic and paradigmatic information in the query expansion process will improve retrieval effectiveness. This article develops and evaluates a new query expansion technique that is based on a formal, corpus-based model of word meaning that models syntagmatic and paradigmatic associations. We demonstrate that when sufficient statistical information exists, as in the case of longer queries, including paradigmatic information alone provides significant improvements in retrieval effectiveness across a wide variety of data sets. More generally, when our new query expansion approach is applied to large-scale web retrieval it demonstrates significant improvements in retrieval effectiveness over a strong baseline system, based on a commercial search engine.

Automatic object segmentation of unstructured scenes using colour and depth maps

This study presents a segmentation pipeline that fuses colour and depth information to automatically separate objects of interest in video sequences captured from a quadcopter. Many approaches assume that cameras are static with known position, a condition which cannot be preserved in most outdoor robotic applications. In this study, the authors compute depth information and camera positions from a monocular video sequence using structure from motion and use this information as an additional cue to colour for accurate segmentation. The authors model the problem similarly to standard segmentation routines as a Markov random field and perform the segmentation using graph cuts optimisation. Manual intervention is minimised and is only required to determine pixel seeds in the first frame which are then automatically reprojected into the remaining frames of the sequence. The authors also describe an automated method to adjust the relative weights for colour and depth according to their discriminative properties in each frame. Experimental results are presented for two video sequences captured using a quadcopter. The quality of the segmentation is compared to a ground truth and other state-of-the-art methods with consistently accurate results.

Designing an innovative approach to engage students in learning science : the evolving case of hybridized writing

Innovations are usually attributed to ideas generated in the minds of individuals. As we reflect upon the evolving design of an online project to engage students in learning science through hybridized writing activities we propose a more distributed view of the process of innovative design. That is, our experience suggests ideas are generated in the activity of interacting with human and material resources that expand and constrain possibilities. This project is innovative in that it is a new educational response to the problem of disengagement of students in science, and has proven to be effective in changing classroom practice and improving students’ scientific literacy. In this chapter, we identify the antecedents and trace the evolution of the project. This account illuminates the innovative design process, presents a summary of the evidence for the effectiveness of the project, and identifies future directions for further development and research. Keywords: Science learning, hybridized writing, case study, innovative approach

Non-linear position control for hover and automatic landing of unmanned aerial vehicles

This study presents a disturbance attenuation controller for horizontal position stabilisation for hover and automatic landings of a rotary-wing unmanned aerial vehicle (RUAV) operating close to the landing deck in rough seas. Based on a helicopter model representing aerodynamics during the landing phase, a non-linear state feedback H∞ controller is designed to achieve rapid horizontal position tracking in a gusty environment. Practical constraints including flapping dynamics, servo dynamics and time lag effect are considered. A high-fidelity closed-loop simulation using parameters of the Vario XLC gas-turbine helicopter verifies performance of the proposed horizontal position controller. The proposed controller not only increases the disturbance attenuation capability of the RUAV, but also enables rapid position response when gusts occur. Comparative studies show that the H∞ controller exhibits performance improvement and can be applied to ship/RUAV landing systems.